Universal approximation bounds for superpositions of a sigmoidal function
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yukich, 1993, Sup norm approximation bounds for networks via Vapnik-Chervonenkis classes
darken, 0, Rate of approximation results motivated b robust neural network learning, Proc Sixth ACM Wrokshop on Computat Learning Theory
stein, 1971, Introduction to Fourier Analysis on Euclidean Spaces
haussler, 1991, Decision theoretic generalizations of the PAC model for neural net and other learning applications
barron, 1988, Statistical learning networks: A unifying view, Proc Symp Interface Statist Comput Sci, 192
tibshirani, 1992, Slide functions for projection pursuit regression and neural networks
zhao, 1992, Projection pursuit learning networks
farago, 1992, Strong universal consistency of neural network classifiers
bellare, 1991, The spectral norm of finite functions
korobov, 1963, Number-Theoretic Methods in Approximate Analysis
rudin, 1984, Real and Complex Analysis
barron, 1992, Neural net approximation, Proc Yale Workshop Adaptive Learning Syst
mccaffrey, 1992, Convergence rates for single hidden layer feedforward networks
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jones, 1991, Good weights and hyperbolic kernels for neural networks projection pursuit and pattern classification Fourier strategies for extracting information from high-dimensional data
pisier, 0, Remarques sur un resultat non publie de ?. Maurey, Proc Seminaire d' analyse fonctionelle 1980-1981